--- license: apache-2.0 base_model: bert-base-uncased tags: - generated_from_trainer metrics: - precision - recall - f1 - accuracy model-index: - name: bert-finetuned-ner results: [] --- # bert-finetuned-ner This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on an unknown dataset. It achieves the following results on the evaluation set: - Loss: 0.0209 - Precision: 0.8249 - Recall: 0.8825 - F1: 0.8527 - Accuracy: 0.9946 - B-location-precision: 0.9446 - B-location-recall: 0.9653 - B-location-f1: 0.9549 - I-location-precision: 0.9358 - I-location-recall: 0.9745 - I-location-f1: 0.9548 - B-group-precision: 0.8819 - B-group-recall: 0.8485 - B-group-f1: 0.8649 - I-group-precision: 0.8879 - I-group-recall: 0.8358 - I-group-f1: 0.8610 - B-corporation-precision: 0.8475 - B-corporation-recall: 0.8552 - B-corporation-f1: 0.8514 - I-corporation-precision: 0.8158 - I-corporation-recall: 0.7294 - I-corporation-f1: 0.7702 - B-person-precision: 0.9583 - B-person-recall: 0.9742 - B-person-f1: 0.9662 - I-person-precision: 0.9596 - I-person-recall: 0.95 - I-person-f1: 0.9548 - B-creative-work-precision: 0.8102 - B-creative-work-recall: 0.7929 - B-creative-work-f1: 0.8014 - I-creative-work-precision: 0.8131 - I-creative-work-recall: 0.8354 - I-creative-work-f1: 0.8241 - B-product-precision: 0.8682 - B-product-recall: 0.7887 - B-product-f1: 0.8266 - I-product-precision: 0.8862 - I-product-recall: 0.8886 - I-product-f1: 0.8874 - Corporation-precision: 0.6972 - Corporation-recall: 0.7919 - Corporation-f1: 0.7415 - Corporation-number: 221 - Creative-work-precision: 0.6433 - Creative-work-recall: 0.7214 - Creative-work-f1: 0.6801 - Creative-work-number: 140 - Group-precision: 0.7465 - Group-recall: 0.8144 - Group-f1: 0.7790 - Group-number: 264 - Location-precision: 0.9026 - Location-recall: 0.9471 - Location-f1: 0.9243 - Location-number: 548 - Person-precision: 0.9101 - Person-recall: 0.9515 - Person-f1: 0.9304 - Person-number: 660 - Product-precision: 0.6908 - Product-recall: 0.7394 - Product-f1: 0.7143 - Product-number: 142 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 0.0002 - train_batch_size: 32 - eval_batch_size: 32 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 3 ### Training results | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy | B-location-precision | B-location-recall | B-location-f1 | I-location-precision | I-location-recall | I-location-f1 | B-group-precision | B-group-recall | B-group-f1 | I-group-precision | I-group-recall | I-group-f1 | B-corporation-precision | B-corporation-recall | B-corporation-f1 | I-corporation-precision | I-corporation-recall | I-corporation-f1 | B-person-precision | B-person-recall | B-person-f1 | I-person-precision | I-person-recall | I-person-f1 | B-creative-work-precision | B-creative-work-recall | B-creative-work-f1 | I-creative-work-precision | I-creative-work-recall | I-creative-work-f1 | B-product-precision | B-product-recall | B-product-f1 | I-product-precision | I-product-recall | I-product-f1 | Corporation-precision | Corporation-recall | Corporation-f1 | Corporation-number | Creative-work-precision | Creative-work-recall | Creative-work-f1 | Creative-work-number | Group-precision | Group-recall | Group-f1 | Group-number | Location-precision | Location-recall | Location-f1 | Location-number | Person-precision | Person-recall | Person-f1 | Person-number | Product-precision | Product-recall | Product-f1 | Product-number | |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|:--------------------:|:-----------------:|:-------------:|:--------------------:|:-----------------:|:-------------:|:-----------------:|:--------------:|:----------:|:-----------------:|:--------------:|:----------:|:-----------------------:|:--------------------:|:----------------:|:-----------------------:|:--------------------:|:----------------:|:------------------:|:---------------:|:-----------:|:------------------:|:---------------:|:-----------:|:-------------------------:|:----------------------:|:------------------:|:-------------------------:|:----------------------:|:------------------:|:-------------------:|:----------------:|:------------:|:-------------------:|:----------------:|:------------:|:---------------------:|:------------------:|:--------------:|:------------------:|:-----------------------:|:--------------------:|:----------------:|:--------------------:|:---------------:|:------------:|:--------:|:------------:|:------------------:|:---------------:|:-----------:|:---------------:|:----------------:|:-------------:|:---------:|:-------------:|:-----------------:|:--------------:|:----------:|:--------------:| | No log | 1.0 | 107 | 0.1175 | 0.5693 | 0.4076 | 0.4751 | 0.9701 | 0.6320 | 0.7646 | 0.6920 | 0.7752 | 0.3929 | 0.5215 | 1.0 | 0.0114 | 0.0225 | 0.6667 | 0.0176 | 0.0343 | 0.9787 | 0.2081 | 0.3433 | nan | 0.0 | nan | 0.8123 | 0.7409 | 0.7750 | 0.9117 | 0.555 | 0.6900 | nan | 0.0 | nan | nan | 0.0 | nan | nan | 0.0 | nan | nan | 0.0 | nan | 0.9787 | 0.2081 | 0.3433 | 221 | 0.0 | 0.0 | 0.0 | 140 | 0.3333 | 0.0152 | 0.0290 | 264 | 0.4682 | 0.6040 | 0.5275 | 548 | 0.6543 | 0.6424 | 0.6483 | 660 | 0.0 | 0.0 | 0.0 | 142 | | No log | 2.0 | 214 | 0.0411 | 0.6931 | 0.7489 | 0.7199 | 0.9886 | 0.8194 | 0.9270 | 0.8699 | 0.8701 | 0.9214 | 0.8950 | 0.7919 | 0.5909 | 0.6768 | 0.6897 | 0.7625 | 0.7242 | 0.8297 | 0.6833 | 0.7494 | 0.8548 | 0.3118 | 0.4569 | 0.9139 | 0.9485 | 0.9309 | 0.8996 | 0.9075 | 0.9035 | 0.7541 | 0.3286 | 0.4577 | 0.7952 | 0.5091 | 0.6208 | 0.7407 | 0.5634 | 0.64 | 0.6740 | 0.8315 | 0.7445 | 0.6515 | 0.5837 | 0.6158 | 221 | 0.2941 | 0.2143 | 0.2479 | 140 | 0.5051 | 0.5682 | 0.5348 | 264 | 0.7617 | 0.8923 | 0.8218 | 548 | 0.8470 | 0.9227 | 0.8832 | 660 | 0.4091 | 0.5070 | 0.4528 | 142 | | No log | 3.0 | 321 | 0.0209 | 0.8249 | 0.8825 | 0.8527 | 0.9946 | 0.9446 | 0.9653 | 0.9549 | 0.9358 | 0.9745 | 0.9548 | 0.8819 | 0.8485 | 0.8649 | 0.8879 | 0.8358 | 0.8610 | 0.8475 | 0.8552 | 0.8514 | 0.8158 | 0.7294 | 0.7702 | 0.9583 | 0.9742 | 0.9662 | 0.9596 | 0.95 | 0.9548 | 0.8102 | 0.7929 | 0.8014 | 0.8131 | 0.8354 | 0.8241 | 0.8682 | 0.7887 | 0.8266 | 0.8862 | 0.8886 | 0.8874 | 0.6972 | 0.7919 | 0.7415 | 221 | 0.6433 | 0.7214 | 0.6801 | 140 | 0.7465 | 0.8144 | 0.7790 | 264 | 0.9026 | 0.9471 | 0.9243 | 548 | 0.9101 | 0.9515 | 0.9304 | 660 | 0.6908 | 0.7394 | 0.7143 | 142 | ### Framework versions - Transformers 4.35.0 - Pytorch 2.1.0+cpu - Datasets 2.14.6 - Tokenizers 0.14.1